Errors drive the evolution of biological signalling to costly codes

Abstract

Reduction of costs in biological signalling seems an evolutionary advantage, but recent experiments have shown signalling codes shifted to signals of high cost with a underutilisation of low cost signals. Here I show that errors in the efficient translation of biological states into signals shift codes to higher costs, effectively performing a quality control. The statistical structure of signal usage is predicted to be of a generalised Boltzmann form that penalises signals that are costly and sensitive to errors. This predicted distribution of signal usage against signal cost has two main features: an exponential tail required for cost efficiency and an underutilisation of the low cost signals required to protect the signalling quality from the errors. These predictions are shown to correspond quantitatively to the experiments in which gathering signal statistics is feasible as in visual cortex neurons.